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文章基本信息

  • 标题:Evaluating Centering for Information Ordering Using Corpora
  • 本地全文:下载
  • 作者:Nikiforos Karamanis ; Chris Mellish ; Massimo Poesio
  • 期刊名称:Computational Linguistics
  • 印刷版ISSN:0891-2017
  • 电子版ISSN:1530-9312
  • 出版年度:2009
  • 卷号:35
  • 期号:1
  • 页码:29-46
  • DOI:10.1162/coli.07-036-R2-06-22
  • 语种:English
  • 出版社:MIT Press
  • 摘要:In this article we discuss several metrics of coherence defined using centering theory and investigate the usefulness of such metrics for information ordering in automatic text generation. We estimate empirically which is the most promising metric and how useful this metric is using a general methodology applied on several corpora. Our main result is that the simplest metric (which relies exclusively on NOCB transitions) sets a robust baseline that cannot be outperformed by other metrics which make use of additional centering-based features. This baseline can be used for the development of both text-to-text and concept-to-text generation systems.
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